Research On Optimization Control Scheme Of Central Heating Pipe Network

With the promotion of the metering and heating system,the user adjusts the terminal temperature control valve according to his own needs,which increases the system instability and puts forward new requirements for the heating operation adjustment.Relying on advanced technologies such as measurement monitoring and information processing,researching the operation strategy of heating system and finding practical and feasible energy-saving control strategy has become an important research direction of heating system regulation and control.Based on the operation data of Luoyang Datang Thermal Power Company,this paper studies the load forecasting method of the secondary network of the heating system and the optimization of the resistance coefficient of the pipe network.The "combination prediction method" and the "variable resistance coefficient optimization identification method" which are more suitable for operation adjustment are proposed,and the optimal control scheme of the heating system is determined based on this.Firstly,the basic principles,modeling process and parameter selection of time series method and support vector regression method widely used in load forecasting are introduced in detail.The two prediction methods were analyzed and evaluated through the actual operation data of Luoyang Datang Thermal Power Company.Considering the advantages and disadvantages of time series method and support vector regression,a load forecasting method for combined forecasting is proposed.The prediction results show that the combined prediction method can make the two models compensate each other in the prediction process,and the prediction error is smaller than the error of the single prediction model,which is more suitable for the accurate load prediction of the heating system.Then the hydraulic calculation model of the heating pipe network is established,based on the principles of mass,energy balance and network graph theory.An optimized identification model and solution method for the variation coefficient of the pipe network under a small number of observation points are proposed.Finally,the heating network simulation model was established.The heat network simulation model was verified by using the pipe network parameters and operation data of the blue sky community of Luoyang Locomotive Factory.The results show that the model has high precision.The pipe network variation resistance coefficient is divided into a fixed pipe resistance coefficient and a variable resistance element resistance coefficient.Bylinearly fitting the data of the valve opening value and the variable resistance element resistance coefficient value,the linear relationship between the valve opening value and the variable resistance element resistance coefficient value is determined.It provides theoretical support for the determination of the set value of the adjustment parameters in the operation regulation of the heating pipe network.Finally,based on the load forecasting and the identification of the resistance coefficient of the pipe network,the optimal control scheme for the heating pipe network is proposed.At the same time,based on the Internet of Things and automatic control technology,combined with the idea of distributed control,the intelligent monitoring system of the heating system is constructed.To achieve the goal of "heat supply on demand,uniform heating".